Smart Airport: Evaluation of Performance Standards and Technologies for a Smart Logistics Zone

2021 ◽  
pp. 036119812110197
Author(s):  
Elifcan Göçmen
Keyword(s):  
Object Detection ◽  
Transportation Planning ◽  
Fuzzy Inference ◽  
Performance Standards ◽  
Inference System ◽  
Suggested Approach ◽  
Smart Logistics ◽  
Baggage Handling ◽  
Smart Technologies ◽  
Smart Airport

Owing to the current context of Industry 4.0, the importance of smart technologies in airport systems have increased substantially. State-of-art applications for transportation planning incorporating baggage services, routing, security, and safety are an evolving domain for both practitioners and researchers dealing with aviation applications. In this context, this paper seeks to answer these questions: Which standards are aimed at a smart airport to make the transportation planning sound? Which propositions are made based on the obtained prioritized standards? This study deals with standards including Environmental Effects, Docking & Navigation, Object Detection & Protection, Communications & Integration, and Terminology using a practical decision support system based on an analytical hierarchy process (AHP) and fuzzy inference system (FIS). Computational results reveal that the Object Detection & Protection standard has an effect on a safe and smart system. To give an overview of this standard for a smart logistics zone (SLZ), an architecture of autonomous robot units and a baggage handling system is proposed in this study. The suggested approach analyzes the obstacle photos obtained by cameras and allows the end-user to control the calculations visually. This research could provide advice to airport planners about smart policies and improving operations.

Integrity Assessment and Control of Offshore Topside Piping: An Expert System Based Approach

2018 ◽  
Author(s):  
R. M. Chandima Ratnayake
Keyword(s):  
Expert System ◽  
Fuzzy Inference ◽  
Control Program ◽  
Technical Condition ◽  
Practical Significance ◽  
Illustrative Case ◽  
Inference System ◽  
Suggested Approach ◽  
Integrity Assessment ◽  
And Control

Downtime has a significant influence on the productive capability of offshore topside operating systems. Integrity assessment and control (IA&C) disciplines face major challenges in implementing a plant integrity control strategy, due to the lack of a methodology for incorporating fuzziness present in the data. To date, the employed IA&C practices face challenges in maintaining uniform quality from one integrity control program to another, due to the variability present in the technical IA&C process, especially among the different integrity assessment experts. Hence, it is vital to use expert systems-based approaches to sustain IA&C activities at an anticipated level and maintain the performance of operating assets at a target level. This manuscript provides a methodology and an illustrative case for how to perform IA&C activities for offshore topside piping. The illustrative case is demonstrated using a fuzzy inference system (FIS). Technical condition (TC) and relative degradation (RD) are selected as the inputs to the FIS for assessing the likelihood of failure (LoF). Expert system-based calculations, and how to use such results for IA&C, are demonstrated. The practical significance of the suggested approach is also discussed.

Aplikasi Peramalan Kebutuhan Beban Listrik Menggunakan Metode Adaptive Neuro Fuzzy Inference System (ANFIS)

2017 ◽  
Vol 3 (1) ◽  
pp. 36-48
Author(s):  
Erwan Ahmad Ardiansyah ◽  
Rina Mardiati ◽  
Afaf Fadhil
Keyword(s):  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Inference System ◽  
Neuro Fuzzy

Prakiraan atau peramalan beban listrik dibutuhkan dalam menentukan jumlah listrik yang dihasilkan. Ini menentukan  agar tidak terjadi beban berlebih yang menyebabkan pemborosan atau kekurangan beban listrik yang mengakibatkan krisis listrik di konsumen. Oleh karena itu di butuhkan prakiraan atau peramalan yang tepat untuk menghasilkan energi listrik. Teknologi softcomputing dapat digunakan  sebagai metode alternatif untuk prediksi beban litrik jangka pendek salah satunya dengan metode  Adaptive Neuro Fuzzy Inference System pada penelitian tugas akhir ini. Data yang di dapat untuk mendukung penelitian ini adalah data dari APD PLN JAWA BARAT yang berisikan laporan data beban puncak bulanan penyulang area gardu induk majalaya dari januari 2011 sampai desember 2014 sebagai data acuan dan data aktual januari-desember 2015. Data kemudian dilatih menggunakan metode ANFIS pada software MATLAB versi b2010. Dari data hasil pelatihan data ANFIS kemudian dilakukan perbandingan dengan data aktual dan data metode regresi meliputi perbandingan anfis-aktual, regresi-aktual dan perbandingan anfis-regresi-aktual. Dari perbandingan disimpulkan bahwa data metode anfis lebih mendekati data aktual dengan rata-rata 1,4%, menunjukan prediksi ANFIS dapat menjadi referensi untuk peramalan beban listrik dimasa depan.

FACE RECOGNITION USING FUZZY INFERENCE SYSTEM

2009 ◽  
Vol 8 (3) ◽  
pp. 887-897
Author(s):  
Vishal Paika ◽  
Er. Pankaj Bhambri
Keyword(s):  
Neural Networks ◽  
Fuzzy Inference ◽  
Facial Features ◽  
Facial Appearance ◽  
Feature Points ◽  
Inference System ◽  
Detection Techniques ◽  
The Face ◽  
Hair Style ◽  
Facial Images

The face is the feature which distinguishes a person. Facial appearance is vital for human recognition. It has certain features like forehead, skin, eyes, ears, nose, cheeks, mouth, lip, teeth etc which helps us, humans, to recognize a particular face from millions of faces even after a large span of time and despite large changes in their appearance due to ageing, expression, viewing conditions and distractions such as disfigurement of face, scars, beard or hair style. A face is not merely a set of facial features but is rather but is rather something meaningful in its form.In this paper, depending on the various facial features, a system is designed to recognize them. To reveal the outline of the face, eyes, ears, nose, teeth etc different edge detection techniques have been used. These features are extracted in the term of distance between important feature points. The feature set obtained is then normalized and are feed to artificial neural networks so as to train them for reorganization of facial images.

ZERO-DAY POLYMORPHIC CYBERATTACKS DETECTION USING FUZZY INFERENCE SYSTEM

2020 ◽  
pp. 8-13
Author(s):  
V. V. Fesokha ◽  
I. Y. Subach ◽  
V. O. Kubrak ◽  
A. V. Mykytiuk ◽  
S. O. Korotaiev
Keyword(s):  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Inference System

IMPLEMENTASI PENENTUAN ARSITEKTUR MASJID MODERN DI ACEH MENGGUNAKAN PEMODELAN SISTEM CERDAS

2018 ◽  
Vol 2 (1) ◽  
Author(s):  
Soraya Masthura Hasan ◽  
T Iqbal Faridiansyah
Keyword(s):  
Fuzzy Inference System ◽  
Architectural Design ◽  
Fuzzy Inference ◽  
Intelligent System ◽  
Selection Process ◽  
System Modeling ◽  
Inference System ◽  
Normal Limits ◽  
Roof Structure ◽  
Selection Of

Mosque architectural design is based on Islamic culture as an approach to objects and products from the Islamic community by looking at their suitability and values and basic principles of Islam that explore more creative and innovative ideas. The purpose of this system is to help the team and the community in seeing the best mosque in the top order so that the system can be used as a reference for the team and the community. The variables used in the selection of modern mosques include facilities and infrastructure, building structure, roof structure, mosque area, level of security and facilities. The system model used is a fuzzy promethee model that is used for the modern mosque selection process. Fuzzy inference assessment is used to determine the value of each variable so that the value remains at normal limits. Fuzzy values will then be included in promethee assessment aspects. The highest promethee ranking results will be made a priority for the best mosque ranking. This fuzzy inference system and promethee system can help the management team and the community in determining the selection of modern mosques in aceh in accordance with modern mosque architecture. Intelligent System Modeling System In Determining Modern Mosque Architecture in the City of Aceh, this building will be web based so that all elements of society can see the best mosque in Aceh by being assessed by all elements of modern mosque architecture.Keywords: Fuzzy inference system, Promethe, Option of  Masjid

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